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Analysis of variability models: a systematic literature review

Abstract

Dealing with variability, during Software Product Line Engineering (SPLE), means trying to allow software engineers to develop a set of similar applications based on a manageable range of variable functionalities according to expert users’ needs. Particularly, variability management (VM) is an activity that allows flexibility and a high level of reuse during software development. In the last years, we have witnessed a proliferation of methods, techniques and supporting tools for VM in general, and for its analysis in particular. More precisely, a specific field has emerged, named (automated) variability analysis, focusing on verifying variability models across the SPLE’s phases. In this paper, we introduce a systematic literature review of existing proposals (as primary studies) focused on analyzing variability models. We define a classification framework, which is composed of 20 sub-characteristics addressing general aspects, such as scope and validation, as well as model-specific aspects, such as variability primitives, reasoner type. The framework allows to look at the analysis of variability models during its whole life cycle—from design to derivation—according to the activities involved during an SPL development. Also, the framework helps us answer three research questions defined for showing the state of the art and drawing challenges for the near future. Among the more interesting challenges, we can highlight the needs of more applications in industry, the existence of more mature tools, and the needs of providing more semantics in the way of variability primitives for identifying inconsistencies in the models.

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Notes

  1. 1.

    A prominent or distinctive user-visible aspect, quality, or characteristic of a software system or systems [36].

  2. 2.

    The ability to perform a task or function.

  3. 3.

    In this paper, proposal and primary study will be used with the same meaning, which is defined in Sect. 9

  4. 4.

    Testing here is understood as an analysis technique that needs to execute the program to analyze a given property.

  5. 5.

    http://fosd.net/spl-strategies/.

  6. 6.

    http://dl.acm.org/.

  7. 7.

    http://ieeexplore.ieee.org/.

  8. 8.

    http://www.sciencedirect.com/.

  9. 9.

    https://scholar.google.com.ar/.

  10. 10.

    https://www.scopus.com/.

  11. 11.

    https://link.springer.com/.

  12. 12.

    http://vamos2014.unice.fr/.

  13. 13.

    http://splc.net/

  14. 14.

    We also checked whether these papers were included in the selected libraries as well.

  15. 15.

    We use the name of the supporting tool provided by the study, when it is specified. Otherwise, we use the surname of the first author.

  16. 16.

    https://www.eclipse.org/.

  17. 17.

    https://www.eclipse.org/modeling/emf/.

  18. 18.

    https://www-01.ibm.com/software/rational/announce.

  19. 19.

    www.sat4j.org/.

  20. 20.

    www.choco-solver.org.

  21. 21.

    https://franz.com/agraph/racer/.

  22. 22.

    http://zotonic.com/.

  23. 23.

    http://www.isa.us.es/fama/?BeTTy_Framework.

  24. 24.

    https://www.ibm.com/support/knowledgecenter/en/SSYQBZ/doors_family_welcome.html.

  25. 25.

    Percentages do not add up to 100 due to some studies belong to more than one classification.

  26. 26.

    This figure was made by assuming that when a study use a language, this language support the scenarios indicated in Table 10 for that study.

  27. 27.

    www.sei.cmu.edu/productlines/.

  28. 28.

    ISO/IEC 26550:2013 Software and systems engineering—Reference model for product line engineering and management.

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Correspondence to Agustina Buccella.

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This work is partially supported by the UNComa Project 04/F009 “Reuso de Software orientado a Dominios—Parte II” part of the program “Desarrollo de Software Basado en Reuso—Parte II”.

Communicated by Andrzej Wasowski.

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Pol’la, M., Buccella, A. & Cechich, A. Analysis of variability models: a systematic literature review. Softw Syst Model 20, 1043–1077 (2021). https://doi.org/10.1007/s10270-020-00839-w

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Keywords

  • Variability analysis
  • Software Product Line
  • Variability management
  • Supporting tools